A predictive model for the thermal conductivity of silty clay soil based on soil porosity and saturation

• Published in: Arabian journal of geosciences Vol. 13; no. 8
• Main Authors: Lyu, Chao, Sun, Qiang, Zhang, Weiqiang, Geng, Jishi
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.04.2020; Springer Nature B.V
• Subjects: Clay; Clay soils; Contact resistance; Density; Earth and Environmental Science; Earth science; Earth Sciences; Field tests; Geology; Geotechnical engineering; Heat conductivity; Heat transfer; Laboratories; Laboratory tests; Linear functions; Moisture content; Original Paper; Porosity; Prediction models; Root-mean-square errors; Saturated soils; Saturation; Soil; Soil density; Soil investigations; Soil porosity; Soil properties; Soil sciences; Tests; Thermal conductivity; Thermal contact resistance; Thermal resistance; Thickness; Water content; Porosity; Soil thermal conductivity; Saturation; Predictive model
• DOI: 10.1007/s12517-020-05284-z
• ISSN: 1866-7511

Soil thermal conductivity is a property that represents a soil’s capability of transferring energy and has been a common subject of study in soil science, geotechnical engineering, and geology. In this study, the quantitative effects of density, water content, saturation, and porosity on thermal conductivity of soil in Fengxian County are investigated by the field and laboratory tests. A new model for predicting soil thermal conductivity from its porosity, saturation, and quartz content is developed. In the field test, the thermal conductivity has a linear relationship with water content due to the increase in thickness of hydration film which decreases the thermal contact resistance between particles. A good logarithmic function is found for the relationship between thermal conductivity and natural density of silty clay soil in Fengxian County. In the laboratory test, there is a linear function for the relationship between thermal conductivity and density of silty clay soil. The thermal conductivity linearly increases with water content and decreases slightly when water content exceeds 17.65% due to the decreased density. The predicted thermal conductivity with the new model is compared with measured thermal conductivity from the field and laboratory tests. The root mean square error (RMSE) of the new model is 0.098 and 0.096 W m −1  K −1 , respectively, which indicates that the new model provides accurate approximations of soil thermal conductivity in Fengxian County, China.